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PubMed2005

[Application of RNAi in gene-deficient models].

RNA interference (RNAi), a process of sequence-specific gene silence,can effectively and specifically suppress the activity of corresponding mRNAs in a gene-dependent manner induced by double-stranded RNA (dsRNA). This powerful technology has been widely employed to manipulate gene expression in mammalian and human cells, elucidate signal transduction pathways and identify gene functions in a whole-genome scale. Simultaneously, it also displays a bright and fascinating future in the research and development of RNAi-based drugs for various diseases such as viral infections, cancers, metabolic disorders and genetic diseases. In present review, we attempt to recapitulate the application of this breakthrough technology in establishing gene-deficient models and show the alluring foreground of RNAi-based gene therapy in these diseases.

Animals↗
PubMed2005

Prokaryotic phylogenies inferred from protein structural domains.

The determination of the phylogenetic relationships among microorganisms has long relied primarily on gene sequence information. Given that prokaryotic organisms often lack morphological characteristics amenable to phylogenetic analysis, prokaryotic phylogenies, in particular, are often based on sequence data. In this work, we explore a new source of phylogenetic information, the distribution of protein structural domains within fully sequenced prokaryotic genomes. The evolution of the structural domains we use has been studied extensively, allowing us to base our phylogenetic methods on testable theoretical models of structural evolution. We find that the methods that produce reasonable phylogenetic relationships are indeed the methods that are most consistent with theoretical evolutionary models. This work represents, to our knowledge, the first such theoretically motivated phylogeny, as well as the first application of structural information to phylogeny on this scale. Our results have strong implications for the phylogenetic relationships among prokaryotic organisms and for the understanding of protein evolution as a whole.

Archaeal Proteins↗
PubMed2005

Immune selection and emergence of aggressive tumor variants as negative consequences of Fas-mediated cytotoxicity and altered IFN-gamma-regulated gene expression.

Antitumor responses can be induced in patients via active or adoptive immunotherapy, yet complete tumor eradication occurs infrequently. This paradox in tumor immunology led us to address two questions: (a) Does an antitumor response, which is intended to destroy the aberrant target population, also at the same time select for aggressive tumor variants (ATV) in vivo? (b) If this process does occur, what is the contribution of the perforin- or Fas-mediated effector mechanism in the immune selection of such ATV? Here, in an experimental mouse lung metastasis model, we showed that ATV generated either naturally in vivo or in vitro by anti-Fas selection resembled each other biologically and genetically as judged by enhanced tumor growth and genome-scale gene expression profiling, respectively. Furthermore, ATV that survived CTL adoptive immunotherapy displayed an even more profound loss of Fas expression and function as well as enhanced malignant proficiency in vivo. ATV, however, retained sensitivity to perforin-mediated lysis in vitro. Lastly, such ATV displayed a diminished responsiveness in their expression of IFN-gamma-regulated genes, including those mechanistically linked to Fas-mediated death (i.e., Fas and caspase-1). Overall, we showed that (a) immune selection did occur in vivo and played an important role in the emergence of ATV, (b) ATV bearing a Fas-resistant phenotype was a chief consequence of immune selection, and (c) an overall diminished responsiveness of IFN-gamma-regulated gene expression was characteristic of ATV. Thus, in this model, Fas-mediated cytotoxicity, in concert with IFN-gamma-regulated gene expression, mechanistically constituted significant determinants of immune selection of ATV in vivo.

Animals↗
PubMed2005

Hybrid and customized approach in telemedicine systems: an unavoidable destination.

Several important problems in the majority of industrialized countries have challenged the centralized and overburdened current model of healthcare. Telehealthcare systems are presented as a new paradigm, offering high expectations to provide effective solutions to this picture. With this paper we present a new methodological approach for telehealthcare systems that pursues the generation of clinical and physiological knowledge of the patient in a real time and personalized manner. This approach is based on a computational component, identified as patient physiological image (PPI), which is responsible for generating an image of the state of the patient and therapy devices. Three key issues of the proposed methodological approach are evaluated. With the objective to validate the capability of the PPI to determine the internal state of a patient, a digital simulation experiment over the mathematical model of a PPI is done. Numerical results are compared to those obtained by a validated mathematical model. Secondly, a laboratory prototype of a novel human physical activity monitor that follows the designed methodological approach will be tested, in order to evaluate the trade-off between processing capacity, portability, and cost-efficiency and power consumption, which are necessary to assure its compliance with the methodology. As a third key issue, the capability of our methodology to integrate physiological information belonging to different scales is analyzed. This is done by means of a case study related to the integration of the regulation of water function of AQP2 channels (genomic, proteomic and cellular levels) into a kidney collecting duct epithelium mathematical model of a PPI. The analysis and preliminary evaluation of the proposed telehealthcare methodological approach, featured by an advanced personalization of health assistance, have been satisfactory.

Delivery of Health Care↗
PubMed2000

The dynamics of repeated elements: applications to the epidemiology of tuberculosis.

We propose a stepwise mutation model to describe the dynamics of DNA fingerprint variation in Mycobacterium tuberculosis. The genome of M. tuberculosis carries insertion sequences (IS6110) that are relatively stable over time periods of months but have an observable transposition rate over longer time scales. Variability in copy number and genomic location of (IS6110) can be harnessed to generate a DNA fingerprint for each strain, by digesting the genome with a restriction enzyme and using a portion of the element as a probe for Southern blots. The number of bands found for a given genome approximates the number of copies of IS6110 it carries. A large data set of such fingerprints from tuberculosis (TB) cases in San Francisco provides an observed distribution of IS6110 copy number. Implementation of the model through deterministic and stochastic simulation indicates some general features of IS/TB dynamics. By comparing observations with outcomes of the model, we conclude that the IS/TB system is very heterogeneous and far from equilibrium. We find that the transposition parameters have a much stronger effect than the epidemic parameters on copy number distribution.

DNA Fingerprinting↗
PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗
PubMed2002

Detecting genomic features under weak selective pressure: the example of codon usage in animals and plants.

Large scale experiments of gene inactivation in yeast have shown that 50% of genes have no detectable impact on the phenotype, and similar observations have been made in other model organisms. This apparent paradox is probably due to the fact that many genes only have a marginal contribution to the fitness of organisms. Because of the size of populations and the number of generations that can be studied in laboratories, experimental approaches only permit to detect functional elements that have a strong phenotypic impact. Comparative sequence analysis can help to solve this problem: the analysis of sequences evolution permits to detect the action of selection, and hence to reveal functional features of genomes. This approach will be illustrated by the study of synonymous codon usage in animals and plants.

Animals↗
PubMed2005

Rat Phenome Project: the untapped potential of existing rat strains.

The National Bio Resource Project for the Rat in Japan collects, preserves, and distributes rat strains. More than 250 inbred strains have been deposited thus far into the National Bio Resource Project for the Rat and are maintained as specific pathogen-free rats or cryopreserved embryos. We are now comprehensively characterizing deposited strains as part of the Rat Phenome Project to reevaluate their value as models of human diseases. Phenotypic data are being collected for 7 categories and 109 parameters: functional observational battery (neurobehavior), behavior studies, blood pressure, biochemical blood tests, hematology, urology, and anatomy. Furthermore, genotypes are being determined for 370 simple sequence-length polymorphism markers distributed through the whole rat genome. Here, we report these large-scale, high-throughput screening data that have already been collected for 54 rat strains. This comprehensive, original phenotypic data can be systematically viewed by "strain ranking" for each parameter. This allows investigators to explore the relationship between several rat strains, to identify new rat models, and to select the most suitable strains for specific experiments. The discovery of several potential models for human diseases, such as hypertension, hypotension, renal diseases, hyperlipemia, hematological disorders, and neurological disorders, illustrates the potential of many existing rat strains. All deposited strains and obtained data are freely available for any interested researcher worldwide at http://www.anim.med.kyoto-u.ac.jp/nbr.

Animals↗
PubMed2006

Finding function in novel targets: C. elegans as a model organism.

Despite its apparent simplicity, the nematode worm Caenorhabditis elegans has developed into an important model for biomedical research, particularly in the functional characterization of novel drug targets that have been identified using genomics technologies. The cellular complexity and the conservation of disease pathways between C. elegans and higher organisms, together with the simplicity and cost-effectiveness of cultivation, make for an effective in vivo model that is amenable to whole-organism high-throughput compound screens and large-scale target validation. This review describes how C. elegans models can be used to advance our understanding of the molecular mechanisms of drug action and disease pathogenesis.

Animals↗
PubMed2003

Identification of the substrates and interaction proteins of aurora kinases from a protein-protein interaction model.

The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. The major need now is to explore this disparate data to find biologically relevant interactions and pathways. Thus, in the post-genomic era, there is clearly a need for the development of algorithms that can accurately predict novel protein-protein interaction networks in silico. The evolutionarily conserved Aurora family kinases have been chosen as a model for the development of a method to identify novel biological networks by a comparison of human and various model organisms. Our search methodology was designed to predict and prioritize molecular targets for Aurora family kinases, so that only the most promising are subjected to empirical testing. Four potential Aurora substrates and/or interacting proteins, TACC3, survivin, Hec1, and hsNuf2, were identified and empirically validated. Together, these results justify the timely implementation of in silico biology in routine wet-lab studies and have also allowed the application of a new approach to the elucidation of protein function in the post-genomic era.

Algorithms↗
PubMed2002

Mice and humans: chromosome engineering and its application to functional genomics.

Functional modeling of human genes and diseases requires suitable mammalian model organisms. For its genetic malleability, the mouse is likely to continue to play a major role in defining basic genetic traits and complex pathological disorders. Recently, gene targeting techniques have been extended towards developing new engineering strategies for generating extensive lesions and rearrangements in mouse chromosomes. While these advances create new opportunities to address similar aberrations observed in human diseases, they also open new ways of scaling-up mutagenesis projects that try to catalogue and annotate cellular functions of mammalian genes.

Animals↗
PubMed2002

MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading.

In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI-BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false-negative rate for yeast-predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein-protein interactions on a genomic scale has been developed.

Algorithms↗
PubMed2005

Delay-induced stochastic oscillations in gene regulation.

The small number of reactant molecules involved in gene regulation can lead to significant fluctuations in intracellular mRNA and protein concentrations, and there have been numerous recent studies devoted to the consequences of such noise at the regulatory level. Theoretical and computational work on stochastic gene expression has tended to focus on instantaneous transcriptional and translational events, whereas the role of realistic delay times in these stochastic processes has received little attention. Here, we explore the combined effects of time delay and intrinsic noise on gene regulation. Beginning with a set of biochemical reactions, some of which are delayed, we deduce a truncated master equation for the reactive system and derive an analytical expression for the correlation function and power spectrum. We develop a generalized Gillespie algorithm that accounts for the non-Markovian properties of random biochemical events with delay and compare our analytical findings with simulations. We show how time delay in gene expression can cause a system to be oscillatory even when its deterministic counterpart exhibits no oscillations. We demonstrate how such delay-induced instabilities can compromise the ability of a negative feedback loop to reduce the deleterious effects of noise. Given the prevalence of negative feedback in gene regulation, our findings may lead to new insights related to expression variability at the whole-genome scale.

Algorithms↗
PubMed2025

Feasibility of using patient navigation to improve identification of hereditary cancer syndromes in newly diagnosed patients with colorectal cancer.

PURPOSE: Germline genetic testing to identify hereditary cancer syndromes in patients newly diagnosed with colorectal cancer (CRC) carries substantial benefits. We examined the feasibility of using patient navigation, an evidence-based approach to reduce structural barriers to recommended care, to improve test completion by increasing pretest counseling attendance. METHODS: We conducted key informant interviews with representatives from organizations providing cancer care to CRC patients. Interviews included questions derived from the Consolidated Framework for Implementation Research, which delineates barriers and facilitators to implementing evidence-based practices. We used an inductive-deductive coding approach to identify themes related to program feasibility. RESULTS: We interviewed 19 participants across 13 organizations. Key feasibility barriers included funding to implement and sustain a navigation program, staffing and supervising the navigator role, health information technology needs, gaining administrators' buy-in, and evolving genetic service delivery models. Participants suggested multiple strategies to address implementation barriers, but most would prefer other approaches to improve genetic test completion over implementing a genomics-focused patient navigation program. CONCLUSION: Stakeholders across a range of health care organizations saw limited value in improving the identification of hereditary CRC syndromes by implementing a program designed to increase pretest genetic counseling attendance. The need to scale up genetic testing has shifted interest toward delivery models better integrated in established care pathways, requiring fewer resources and providing broader reach.

Humans↗
PubMed2000

The physics of DNA and the annotation of the Plasmodium falciparum genome.

A gene identification procedure is formulated, based on large-scale structural analyses of genomic sequences. The structural property is the physical - thermal - stability of the DNA double-helix, as described by the classical helix-coil model. The analyses are detailed for the Plasmodium falciparum genome, which represents one of the most difficult cases for the gene identification problem (notably because of the extreme AT-richness of the genome). In this genome, the coding domains (either uninterrupted genes or exons in split genes) are accurately identified as regions of high thermal stability. The conclusion is based on the study of the available cloned genes, of which 17 examples are described in detail. These examples demonstrate that the physical criterion is valid for the detection of coding regions whose lengths extend from a few base pairs up to several thousand base pairs. Accordingly, the structural analyses can provide a powerful and convenient tool for the identification of complex genes in the P. falciparum genome. The limits of such a scheme are discussed. The gene identification procedure is applied to the completely sequenced chromosomes (2 and 3), and the results are compared with the database annotations. The structural analyses suggest more or less extensive revision to the annotations, and also allow new putative genes to be identified in the chromosome sequences. Several examples of such new genes are described in detail.

Animals↗
PubMedDate not supplied

Robust method for proteome analysis by MS/MS using an entire translated genome: demonstration on the ciliome of Tetrahymena thermophila.

To improve the utility of increasingly large numbers of available unannotated and initially poorly annotated genomic sequences for proteome analysis, we demonstrate that effective protein identification can be made on a large and unannotated genome. The strategy developed is to translate the unannotated genome sequence into amino acid sequence encoding putative proteins in all six reading frames, to identify peptides by tandem mass spectrometry (MS/MS), to localize them on the genome sequence, and to preliminarily annotate the protein via a similarity search by BLAST. These tasks have been optimized and automated. Optimization to obtain multiple peptide matches in effect extends the searchable region and results in more robust protein identification. The viability of this strategy is demonstrated with the identification of 223 cilia proteins in the unicellular eukaryotic model organism Tetrahymena thermophila, whose initial genomic sequence draft was released in November 2003. To the best of our knowledge, this is the first demonstration of large-scale protein identification based on such a large, unannotated genome. Of the 223 cilia proteins, 84 have no similarity to proteins in NCBI's nonredundant (nr) database. This methodology allows identifying the locations of the genes encoding these novel proteins, which is a necessary first step to downstream functional genomic experimentation.

Amino Acid Sequence↗
PubMed2005

Munich information center for protein sequences plant genome resources: a framework for integrative and comparative analyses 1(W).

With several plant genomes sequenced, the power of comparative genome analysis can now be applied. However, genome-scale cross-species analyses are limited by the effort for data integration. To develop an integrated cross-species plant genome resource, we maintain comprehensive databases for model plant genomes, including Arabidopsis (Arabidopsis thaliana), maize (Zea mays), Medicago truncatula, and rice (Oryza sativa). Integration of data and resources is emphasized, both in house as well as with external partners and databases. Manual curation and state-of-the-art bioinformatic analysis are combined to achieve quality data. Easy access to the data is provided through Web interfaces and visualization tools, bulk downloads, and Web services for application-level access. This allows a consistent view of the model plant genomes for comparative and evolutionary studies, the transfer of knowledge between species, and the integration with functional genomics data.

Computational Biology↗
PubMed2005

How will RNAi facilitate drug development?

Development of effective drugs for treatment of human disease relies on identification of therapeutic molecular targets. The identification of targets to treat human disease has previously relied on genetic screens in model organisms, and less robust or lower throughput approaches in mammalian systems. RNA interference (RNAi) makes possible, for the first time, the use of large-scale functional genomics approaches for target identification in human cells. This remarkable breakthrough has the potential to influence every facet of the drug discovery process, and is poised to revolutionize drug development. Reports of RNAi screens for the identification of novel genes implicated in apoptosis, cell division, and drug resistance support the enormous promise of this technology. Here, we discuss the potential impact of RNAi screens on target identification and validation and consider issues that warrant caution when interpreting RNAi screening results.

Animals↗